Faceted searches are powerful tools that allow the results to be categorized so that the user can further narrow the search quickly and easily. Thus, in this manner, the faceted search provides a simple means for users to add criteria to a search to help narrow the results.
By way of example, during a faceted search, the user is capable of browsing through the search results, while still permitting further narrowing of the search by adding additional criteria to the search. In addition to providing lists of pages that match a keyword search, faceted search shows lists of categories that contain matching pages. With the lists of categories, the user can then select one or more categories to narrow their search.
As thus, it has been found by many Internet retailers that the use of faceted searches is a very powerful tool. In such applications, the faceted search can provide, for example,                Displaying aspects of the current results set in multiple categorization schemes;        The ability for the user to use a point-and-click approach for narrowing the search based on the characteristics being sought (e.g., type of item, color, features, cost);        Showing only populated categories; and/or        Displaying a count of the contents of each category.For these and other reasons, the faceted search is growing quickly on the World Wide Web, and a number of the better-known retail sites have already adopted such searching tools, such as, for example, amazon.com, Sears, Wal-Mart and other large retailers.        
Faceted searches, though, have potential shortcoming that must still be addressed. For example, the number of possible matching categories can be very large, which complicates the search. Another shortcoming is that, in many cases, the categories have sub-categories so that focusing in on the desired category may take the user through multiple levels, e.g., many hyperlinks or mouse “clicks”. For example, to see the category “Chairs and Recliners”, the user may first have to click “Furniture and Decor”, then “Sofas, Love Seats, & Chairs”, and finally “Chairs and Recliners”. Finally, users with known interests across multiple taxonomies (e.g., music interests which are “blues” and “CDs” and “$15-$20”) must take multiple steps to narrow their search across multiple taxonomies.
Thus, although faceted searches make it much easier for users to search through a specific database, producing effective search queries still remains difficult and elusive to many users. Simply, the efficacy of a faceted search depends on the speed with which a user can find the categories of interest. But, there are many issues that may impact the speed of the search: “breadth of categories”, “depth of categories”, and “cross-taxonomy interaction.”
Breadth of Categories
By way of illustration, there may be countless categories (e.g., 50 or more categories) for a user to choose during the search. In these cases, one of the categories of interest may be, literally, one of the last categories, which requires the user to scroll through the majority of categories prior to obtaining the desired category of interest. Thus, in order to narrow the search, the user would need to scroll through almost each and every category.
Depth of Categories
When categories are hierarchically organized, users may have to “drill down” into categories to find the sub-category of interest. This is the case even though the user already knows and has regularly visited the desired category. For example, suppose a Political Science student wants to find a Political Science book on a certain retailer's website. Although the student cannot recall the specific title, she does remember that the title has the word “file”. To begin, the student:                (i) starts a search with the word “file”;        (ii) scrolls down to “Books” (e.g., category #11), and clicks the link, limiting the results to books with “file” in the description; and        (iii) scrolls down to Political Science (e.g., category #10) and clicks the link, limiting the results to Political Science books with “file” in the description.Thus, even though the user had a well-known interest when coming to the site, the user still had to click multiple times to access the desired category. Of course, although two clicks does not seem extreme, this can quickly become frustrating if the user regularly uses the site and is frequently interested in that category.        
These issues are likely to become more pronounced as faceted searches become ubiquitous; including moving into business and especially large databases (e.g., breadth/depth of categories of the Library of Congress). In fact, the examples above are in many ways the simplest case, and do not illustrate the final issue of “cross-taxonomy interaction”.
Cross-Taxonomy Interaction
In some cases, users may want to refine a search by selecting subcategories from different taxonomies. The issue here is much like depth of categories, except that with each successive category selection, the remaining category changes to reflect the new result set.
By way of illustration, suppose a music-lover is interested in Blues music, and only buys CDs. In this example, the user hears a song on the radio, but only hears the artist's last name, Davis, for example. Now, at a large retail website, the user performs a search on “Davis”, and obtains a large number of songs. One at a time, the user must make a selection from the “Genre” category (Blues), and from the “Format” category (CD) to narrow the search. This can be frustrating to the user.
Accordingly, there exists a need in the art to overcome the deficiencies and limitations described hereinabove.